We note that, in contrast to the hidden state that is common in real-world problems [1]}, [2]}, [3]}, standard benchmarks like the PyBullet suite [4]} are fully observed, enabling off-policy algorithms like behavioral cloning to match expert performance [5]}. Thus, for our experiments, we introduce partial observability to ensure that we are focused on part of what makes imitation learning hard in practice.
